code: def evaluate(self, points):
      check_arraylike("evaluate", points)
      points = self._reshape_points(points)
      result = _gaussian_kernel_eval(
          False,
          self.dataset.T,
          self.weights[:, None],
          points.T,
          self.inv_cov,
      )
      return result[:, 0]
  
imports: from dataclasses import dataclass
  from functools import partial
  from typing import Any
  import numpy
  import scipy.stats
  import jax.numpy
  from jax import jit, lax, random, vmap
  from jax._src.numpy.util import check_arraylike, promote_dtypes_inexact, _wraps
  from jax._src.tree_util import register_pytree_node_class
  from jax.scipy import linalg, special
label_desc: Use image node_id 7 for calling the gaussian_kde obj's underlying member method code with example usage: obj.evaluate(points) and returns: result